Symbols of Hope on Pediatric Oncology Ward: Children's Perspective Using Photovoice
Bibliographic record
Abstract
Background Hope nurtures confidence and enhances positivity. It is known to be a critical factor in illness, recovery and healing. This study aimed to identify the views of hospitalized children with cancer about the circumstances and factors that create hope for them in the oncology ward. Methods: This qualitative study explored children's experiences using Photovoice, which is an arts-based approach. Twenty children aged 6–12 years diagnosed with various cancers at a Pediatric Hospital in Tehran, Iran, participated in this study. Participants were requested to take photographs of objects, circumstances, or anything that gave them hope or represented a sign of hope in the oncology ward. The photographs were then used to facilitate face-to-face interviews with these children. Data were analyzed using thematic analysis. Results: Data analysis revealed six main themes: emotional connectedness with nursing staff; the playroom as a means to soften the hospital space; the presence of a parent; symbols of recovery; a touch of nature in the hospital setting; and escaping the hospital cage. Discussion: Hopefulness among children can emanate from diverse events and circumstances within the hospital environment. Nurses and physicians need an understanding of children's perspectives to design interventions to improve hopefulness among hospitalized children with cancer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".